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Record W4385757076 · doi:10.1051/0004-6361/202346066

In pursuit of giants

2023· article· en· W4385757076 on OpenAlexafffund
D. Donevski, Ivana Damjanov, A. Nanni, Allison W. S. Man, Marika Giulietti, Michael Romano, Andrea Lapi, Desika Narayanan, Romeel Davé, Irene Shivaei, Jubee Sohn, L. Pantoni, Qi Li

Bibliographic record

VenueAstronomy and Astrophysics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of British ColumbiaSaint Mary's University
FundersNatural Sciences and Engineering Research Council of CanadaNarodowe Centrum NaukiNational Science Foundation
KeywordsPhysicsAstrophysicsMetallicityGalaxyStar formationStellar massAstronomyRedshiftInterstellar mediumStellar populationPopulationGalaxy formation and evolutionStars

Abstract

fetched live from OpenAlex

The physical mechanisms that link the termination of star formation in quiescent galaxies and the evolution of their baryonic components, stars, and the interstellar medium (ISM; dust, gas, and metals) are poorly constrained beyond the local Universe. In this work, we characterise the evolution of the dust content in 545 quiescent galaxies observed at 0.1 < z < 0.6 as part of the hCOSMOS spectroscopic redshift survey. This is, to date, the largest sample of quiescent galaxies at intermediate redshifts for which the dust, stellar, and metal abundances are consistently estimated. We analyse how the crucial markers of a galaxy dust life cycle, such as specific dust mass ( M dust / M ⋆ ), evolve with different physical parameters, namely gas-phase metallicity ( Z gas ), time since quenching ( t quench ), stellar mass ( M ⋆ ), and stellar population age. We find morphology to be an important factor in the large scatter in M dust / M ⋆ (∼2 orders of magnitude). Quiescent spirals exhibit strong evolutionary trends of specific dust mass with M ⋆ , stellar age, and galaxy size, in contrast to the little to no evolution experienced by ellipticals. When transitioning from solar to super-solar metallicities (8.7 ≲ 12 + log(O/H)≲9.1), quiescent spirals undergo a reversal in M dust / M ⋆ , indicative of a change in dust production efficiency. By modelling the star formation histories of our objects, we unveil a broad dynamical range of post-quenching timescales (60 Myr < t quench < 3.2 Gyr). We show that M dust / M ⋆ is highest in recently quenched systems ( t quench < 500 Myr), but its further evolution is non-monotonic, as a consequence of different pathways for dust formation, growth, or removal on various timescales. Our data are best described by simulations that include dust growth in the ISM. While this process is prevalent in the majority of galaxies, for ∼15% of objects we find evidence of additional dust content acquired externally, most likely via minor mergers. Altogether, our results strongly suggest that prolonged dust production on a timescale of 0.5 − 1 Gyr since quenching may be common in dusty quiescent galaxies at intermediate redshifts, even if their gas reservoirs are heavily exhausted (i.e. cold gas fraction < 1 − 5%).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.008

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.207
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2023
Admission routes2
Has abstractyes

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